EbadKhan commited on
Commit
7b41041
1 Parent(s): 79f8665

Upload FalconForCausalLM

Browse files
README.md ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags: []
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+ This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+
201
+
config.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "tiiuae/falcon-7b-instruct",
3
+ "alibi": false,
4
+ "apply_residual_connection_post_layernorm": false,
5
+ "architectures": [
6
+ "FalconForCausalLM"
7
+ ],
8
+ "attention_dropout": 0.0,
9
+ "auto_map": {
10
+ "AutoConfig": "tiiuae/falcon-7b-instruct--configuration_falcon.FalconConfig",
11
+ "AutoModel": "tiiuae/falcon-7b-instruct--modeling_falcon.FalconModel",
12
+ "AutoModelForCausalLM": "tiiuae/falcon-7b-instruct--modeling_falcon.FalconForCausalLM",
13
+ "AutoModelForQuestionAnswering": "tiiuae/falcon-7b-instruct--modeling_falcon.FalconForQuestionAnswering",
14
+ "AutoModelForSequenceClassification": "tiiuae/falcon-7b-instruct--modeling_falcon.FalconForSequenceClassification",
15
+ "AutoModelForTokenClassification": "tiiuae/falcon-7b-instruct--modeling_falcon.FalconForTokenClassification"
16
+ },
17
+ "bias": false,
18
+ "bos_token_id": 11,
19
+ "eos_token_id": 11,
20
+ "hidden_dropout": 0.0,
21
+ "hidden_size": 4544,
22
+ "initializer_range": 0.02,
23
+ "layer_norm_epsilon": 1e-05,
24
+ "model_type": "falcon",
25
+ "multi_query": true,
26
+ "new_decoder_architecture": false,
27
+ "num_attention_heads": 71,
28
+ "num_hidden_layers": 32,
29
+ "num_kv_heads": 71,
30
+ "parallel_attn": true,
31
+ "torch_dtype": "float16",
32
+ "transformers_version": "4.39.0.dev0",
33
+ "use_cache": true,
34
+ "vocab_size": 65024
35
+ }
generation_config.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 11,
4
+ "eos_token_id": 11,
5
+ "transformers_version": "4.39.0.dev0"
6
+ }
model-00001-of-00003.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c15b3b58b083e940bc78b73b9699867025fa4a720509ae02df5575dc1a7a314e
3
+ size 4981285784
model-00002-of-00003.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:659fa966c9a37b4af317f42c731509a2bcff051f6b45923fe44478bbcb6c4ce9
3
+ size 4969690496
model-00003-of-00003.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8ebd645b661e9c3ada1ec71da8e5546f0ae067c50e8dd5cb42b6a55520488296
3
+ size 3892488240
model.safetensors.index.json ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 13843441408
4
+ },
5
+ "weight_map": {
6
+ "transformer.h.0.input_layernorm.bias": "model-00001-of-00003.safetensors",
7
+ "transformer.h.0.input_layernorm.weight": "model-00001-of-00003.safetensors",
8
+ "transformer.h.0.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
9
+ "transformer.h.0.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
10
+ "transformer.h.0.self_attention.dense.weight": "model-00001-of-00003.safetensors",
11
+ "transformer.h.0.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
12
+ "transformer.h.1.input_layernorm.bias": "model-00001-of-00003.safetensors",
13
+ "transformer.h.1.input_layernorm.weight": "model-00001-of-00003.safetensors",
14
+ "transformer.h.1.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
15
+ "transformer.h.1.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
16
+ "transformer.h.1.self_attention.dense.weight": "model-00001-of-00003.safetensors",
17
+ "transformer.h.1.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
18
+ "transformer.h.10.input_layernorm.bias": "model-00002-of-00003.safetensors",
19
+ "transformer.h.10.input_layernorm.weight": "model-00002-of-00003.safetensors",
20
+ "transformer.h.10.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
21
+ "transformer.h.10.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
22
+ "transformer.h.10.self_attention.dense.weight": "model-00001-of-00003.safetensors",
23
+ "transformer.h.10.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
24
+ "transformer.h.11.input_layernorm.bias": "model-00002-of-00003.safetensors",
25
+ "transformer.h.11.input_layernorm.weight": "model-00002-of-00003.safetensors",
26
+ "transformer.h.11.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
27
+ "transformer.h.11.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
28
+ "transformer.h.11.self_attention.dense.weight": "model-00002-of-00003.safetensors",
29
+ "transformer.h.11.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
30
+ "transformer.h.12.input_layernorm.bias": "model-00002-of-00003.safetensors",
31
+ "transformer.h.12.input_layernorm.weight": "model-00002-of-00003.safetensors",
32
+ "transformer.h.12.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
33
+ "transformer.h.12.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
34
+ "transformer.h.12.self_attention.dense.weight": "model-00002-of-00003.safetensors",
35
+ "transformer.h.12.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
36
+ "transformer.h.13.input_layernorm.bias": "model-00002-of-00003.safetensors",
37
+ "transformer.h.13.input_layernorm.weight": "model-00002-of-00003.safetensors",
38
+ "transformer.h.13.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
39
+ "transformer.h.13.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
40
+ "transformer.h.13.self_attention.dense.weight": "model-00002-of-00003.safetensors",
41
+ "transformer.h.13.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
42
+ "transformer.h.14.input_layernorm.bias": "model-00002-of-00003.safetensors",
43
+ "transformer.h.14.input_layernorm.weight": "model-00002-of-00003.safetensors",
44
+ "transformer.h.14.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
45
+ "transformer.h.14.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
46
+ "transformer.h.14.self_attention.dense.weight": "model-00002-of-00003.safetensors",
47
+ "transformer.h.14.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
48
+ "transformer.h.15.input_layernorm.bias": "model-00002-of-00003.safetensors",
49
+ "transformer.h.15.input_layernorm.weight": "model-00002-of-00003.safetensors",
50
+ "transformer.h.15.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
51
+ "transformer.h.15.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
52
+ "transformer.h.15.self_attention.dense.weight": "model-00002-of-00003.safetensors",
53
+ "transformer.h.15.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
54
+ "transformer.h.16.input_layernorm.bias": "model-00002-of-00003.safetensors",
55
+ "transformer.h.16.input_layernorm.weight": "model-00002-of-00003.safetensors",
56
+ "transformer.h.16.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
57
+ "transformer.h.16.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
58
+ "transformer.h.16.self_attention.dense.weight": "model-00002-of-00003.safetensors",
59
+ "transformer.h.16.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
60
+ "transformer.h.17.input_layernorm.bias": "model-00002-of-00003.safetensors",
61
+ "transformer.h.17.input_layernorm.weight": "model-00002-of-00003.safetensors",
62
+ "transformer.h.17.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
63
+ "transformer.h.17.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
64
+ "transformer.h.17.self_attention.dense.weight": "model-00002-of-00003.safetensors",
65
+ "transformer.h.17.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
66
+ "transformer.h.18.input_layernorm.bias": "model-00002-of-00003.safetensors",
67
+ "transformer.h.18.input_layernorm.weight": "model-00002-of-00003.safetensors",
68
+ "transformer.h.18.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
69
+ "transformer.h.18.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
70
+ "transformer.h.18.self_attention.dense.weight": "model-00002-of-00003.safetensors",
71
+ "transformer.h.18.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
72
+ "transformer.h.19.input_layernorm.bias": "model-00002-of-00003.safetensors",
73
+ "transformer.h.19.input_layernorm.weight": "model-00002-of-00003.safetensors",
74
+ "transformer.h.19.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
75
+ "transformer.h.19.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
76
+ "transformer.h.19.self_attention.dense.weight": "model-00002-of-00003.safetensors",
77
+ "transformer.h.19.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
78
+ "transformer.h.2.input_layernorm.bias": "model-00001-of-00003.safetensors",
79
+ "transformer.h.2.input_layernorm.weight": "model-00001-of-00003.safetensors",
80
+ "transformer.h.2.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
81
+ "transformer.h.2.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
82
+ "transformer.h.2.self_attention.dense.weight": "model-00001-of-00003.safetensors",
83
+ "transformer.h.2.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
84
+ "transformer.h.20.input_layernorm.bias": "model-00002-of-00003.safetensors",
85
+ "transformer.h.20.input_layernorm.weight": "model-00002-of-00003.safetensors",
86
+ "transformer.h.20.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
87
+ "transformer.h.20.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
88
+ "transformer.h.20.self_attention.dense.weight": "model-00002-of-00003.safetensors",
89
+ "transformer.h.20.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
90
+ "transformer.h.21.input_layernorm.bias": "model-00002-of-00003.safetensors",
91
+ "transformer.h.21.input_layernorm.weight": "model-00002-of-00003.safetensors",
92
+ "transformer.h.21.mlp.dense_4h_to_h.weight": "model-00002-of-00003.safetensors",
93
+ "transformer.h.21.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
94
+ "transformer.h.21.self_attention.dense.weight": "model-00002-of-00003.safetensors",
95
+ "transformer.h.21.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
96
+ "transformer.h.22.input_layernorm.bias": "model-00003-of-00003.safetensors",
97
+ "transformer.h.22.input_layernorm.weight": "model-00003-of-00003.safetensors",
98
+ "transformer.h.22.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
99
+ "transformer.h.22.mlp.dense_h_to_4h.weight": "model-00002-of-00003.safetensors",
100
+ "transformer.h.22.self_attention.dense.weight": "model-00002-of-00003.safetensors",
101
+ "transformer.h.22.self_attention.query_key_value.weight": "model-00002-of-00003.safetensors",
102
+ "transformer.h.23.input_layernorm.bias": "model-00003-of-00003.safetensors",
103
+ "transformer.h.23.input_layernorm.weight": "model-00003-of-00003.safetensors",
104
+ "transformer.h.23.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
105
+ "transformer.h.23.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
106
+ "transformer.h.23.self_attention.dense.weight": "model-00003-of-00003.safetensors",
107
+ "transformer.h.23.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
108
+ "transformer.h.24.input_layernorm.bias": "model-00003-of-00003.safetensors",
109
+ "transformer.h.24.input_layernorm.weight": "model-00003-of-00003.safetensors",
110
+ "transformer.h.24.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
111
+ "transformer.h.24.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
112
+ "transformer.h.24.self_attention.dense.weight": "model-00003-of-00003.safetensors",
113
+ "transformer.h.24.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
114
+ "transformer.h.25.input_layernorm.bias": "model-00003-of-00003.safetensors",
115
+ "transformer.h.25.input_layernorm.weight": "model-00003-of-00003.safetensors",
116
+ "transformer.h.25.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
117
+ "transformer.h.25.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
118
+ "transformer.h.25.self_attention.dense.weight": "model-00003-of-00003.safetensors",
119
+ "transformer.h.25.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
120
+ "transformer.h.26.input_layernorm.bias": "model-00003-of-00003.safetensors",
121
+ "transformer.h.26.input_layernorm.weight": "model-00003-of-00003.safetensors",
122
+ "transformer.h.26.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
123
+ "transformer.h.26.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
124
+ "transformer.h.26.self_attention.dense.weight": "model-00003-of-00003.safetensors",
125
+ "transformer.h.26.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
126
+ "transformer.h.27.input_layernorm.bias": "model-00003-of-00003.safetensors",
127
+ "transformer.h.27.input_layernorm.weight": "model-00003-of-00003.safetensors",
128
+ "transformer.h.27.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
129
+ "transformer.h.27.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
130
+ "transformer.h.27.self_attention.dense.weight": "model-00003-of-00003.safetensors",
131
+ "transformer.h.27.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
132
+ "transformer.h.28.input_layernorm.bias": "model-00003-of-00003.safetensors",
133
+ "transformer.h.28.input_layernorm.weight": "model-00003-of-00003.safetensors",
134
+ "transformer.h.28.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
135
+ "transformer.h.28.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
136
+ "transformer.h.28.self_attention.dense.weight": "model-00003-of-00003.safetensors",
137
+ "transformer.h.28.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
138
+ "transformer.h.29.input_layernorm.bias": "model-00003-of-00003.safetensors",
139
+ "transformer.h.29.input_layernorm.weight": "model-00003-of-00003.safetensors",
140
+ "transformer.h.29.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
141
+ "transformer.h.29.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
142
+ "transformer.h.29.self_attention.dense.weight": "model-00003-of-00003.safetensors",
143
+ "transformer.h.29.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
144
+ "transformer.h.3.input_layernorm.bias": "model-00001-of-00003.safetensors",
145
+ "transformer.h.3.input_layernorm.weight": "model-00001-of-00003.safetensors",
146
+ "transformer.h.3.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
147
+ "transformer.h.3.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
148
+ "transformer.h.3.self_attention.dense.weight": "model-00001-of-00003.safetensors",
149
+ "transformer.h.3.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
150
+ "transformer.h.30.input_layernorm.bias": "model-00003-of-00003.safetensors",
151
+ "transformer.h.30.input_layernorm.weight": "model-00003-of-00003.safetensors",
152
+ "transformer.h.30.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
153
+ "transformer.h.30.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
154
+ "transformer.h.30.self_attention.dense.weight": "model-00003-of-00003.safetensors",
155
+ "transformer.h.30.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
156
+ "transformer.h.31.input_layernorm.bias": "model-00003-of-00003.safetensors",
157
+ "transformer.h.31.input_layernorm.weight": "model-00003-of-00003.safetensors",
158
+ "transformer.h.31.mlp.dense_4h_to_h.weight": "model-00003-of-00003.safetensors",
159
+ "transformer.h.31.mlp.dense_h_to_4h.weight": "model-00003-of-00003.safetensors",
160
+ "transformer.h.31.self_attention.dense.weight": "model-00003-of-00003.safetensors",
161
+ "transformer.h.31.self_attention.query_key_value.weight": "model-00003-of-00003.safetensors",
162
+ "transformer.h.4.input_layernorm.bias": "model-00001-of-00003.safetensors",
163
+ "transformer.h.4.input_layernorm.weight": "model-00001-of-00003.safetensors",
164
+ "transformer.h.4.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
165
+ "transformer.h.4.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
166
+ "transformer.h.4.self_attention.dense.weight": "model-00001-of-00003.safetensors",
167
+ "transformer.h.4.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
168
+ "transformer.h.5.input_layernorm.bias": "model-00001-of-00003.safetensors",
169
+ "transformer.h.5.input_layernorm.weight": "model-00001-of-00003.safetensors",
170
+ "transformer.h.5.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
171
+ "transformer.h.5.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
172
+ "transformer.h.5.self_attention.dense.weight": "model-00001-of-00003.safetensors",
173
+ "transformer.h.5.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
174
+ "transformer.h.6.input_layernorm.bias": "model-00001-of-00003.safetensors",
175
+ "transformer.h.6.input_layernorm.weight": "model-00001-of-00003.safetensors",
176
+ "transformer.h.6.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
177
+ "transformer.h.6.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
178
+ "transformer.h.6.self_attention.dense.weight": "model-00001-of-00003.safetensors",
179
+ "transformer.h.6.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
180
+ "transformer.h.7.input_layernorm.bias": "model-00001-of-00003.safetensors",
181
+ "transformer.h.7.input_layernorm.weight": "model-00001-of-00003.safetensors",
182
+ "transformer.h.7.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
183
+ "transformer.h.7.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
184
+ "transformer.h.7.self_attention.dense.weight": "model-00001-of-00003.safetensors",
185
+ "transformer.h.7.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
186
+ "transformer.h.8.input_layernorm.bias": "model-00001-of-00003.safetensors",
187
+ "transformer.h.8.input_layernorm.weight": "model-00001-of-00003.safetensors",
188
+ "transformer.h.8.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
189
+ "transformer.h.8.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
190
+ "transformer.h.8.self_attention.dense.weight": "model-00001-of-00003.safetensors",
191
+ "transformer.h.8.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
192
+ "transformer.h.9.input_layernorm.bias": "model-00001-of-00003.safetensors",
193
+ "transformer.h.9.input_layernorm.weight": "model-00001-of-00003.safetensors",
194
+ "transformer.h.9.mlp.dense_4h_to_h.weight": "model-00001-of-00003.safetensors",
195
+ "transformer.h.9.mlp.dense_h_to_4h.weight": "model-00001-of-00003.safetensors",
196
+ "transformer.h.9.self_attention.dense.weight": "model-00001-of-00003.safetensors",
197
+ "transformer.h.9.self_attention.query_key_value.weight": "model-00001-of-00003.safetensors",
198
+ "transformer.ln_f.bias": "model-00003-of-00003.safetensors",
199
+ "transformer.ln_f.weight": "model-00003-of-00003.safetensors",
200
+ "transformer.word_embeddings.weight": "model-00001-of-00003.safetensors"
201
+ }
202
+ }